The integration of artificial intelligence (AI) in education presents significant challenges, such as gaps in educators' digital adaptability, ethical considerations, and inconsistent infrastructure. This study details the development and validation of the Insan AI Platform, an integrated learning solution designed to address these obstacles through adaptive AI tools for both teachers and students. The platform was developed using a user-centered prototyping methodology, drawing on comprehensive literature analysis, Focus Group Discussions with 26 educational stakeholders, and expert interviews. Key features include an AI Content Generator, a Virtual Tutor, and a Learning Analytics dashboard, all intended to facilitate personalized learning experiences and enhance teaching efficiency. User Acceptance Testing with 20 teachers demonstrated the platform's functional robustness, with perfect pass rates on all core features and a high usability score (SUS: 84.0). The platform architecture integrates multiple AI application programming interfaces (APIs) while maintaining responsive performance under varied network conditions. These findings indicate that the Insan AI Platform effectively meets user requirements and provides a strong foundation for broader educational implementation. Future development will focus on incorporating multilingual support and advanced learning analytics capabilities. According to a questionnaire completed by 26 users, there was a score increase of 22.42 after using the Insan AI platform. This indicates that the application has successfully met user requirements

Many study programs at universities face issues, including students experiencing delays in graduation, which hinders the completion of their studies on time. These delays in student graduation contribute to a decrease in the accreditation score of the Information Systems program. One solution to address this issue is to develop a data-mining-based system to monitor and utilize student progress data by predicting their graduation status using the C4.5 Decision Tree algorithm. This research process involves several stages: problem analysis, data and system design, coding, testing, and finally, maintenance. The outcome of this research is the implementation of the C4.5 algorithm to predict students' timely and delayed graduation. The data used includes records of students who graduated in 2021 and 2022. The acceptance rate, calculated using a confusion matrix, demonstrates an accuracy level of 92.16%, based on a dataset of 119 training data points and 51 testing data points, or 70% training to 30% testing ratio. The results of this research and testing indicate that the C4.5 Decision Tree algorithm is highly suitable for predicting student graduation outcomes.

Currently attendance is still done manually by recapping each lecturer's attendance sheet. The method used is the prototype method and testing using the User Acceptant Test (UAT) method. This takes a long time, even misinterpretations of existing absences sometimes cause problems when giving salary receipts to lecturers, besides that, reporting to campus management also takes time. The lecturer attendance system can help the finance department to calculate lecturer teaching attendance faster and more easily, which can be used to calculate salaries and evaluate lecturer attendance. The system at the implementation stage and during implementation the average teaching attendance of lecturers is easier to control. Some of the features in this attendance system include Check-in, Lecturer, profile, History, Schedule, Help, Tutorial and Chat Group. Apart from that, the main menu also provides information regarding the check-in time limit, waiting time for the next check-in, campus information, and application updates. The system was built with a QR Code and is Android-based to make things easier for lecturers, admin, and the finance department.

The problem in the learning community in the culinary field is that there is still a lot of cooking knowledge that is lost because the person concerned dies before being inherited, the many types of dishes that are still separated in small groups, the emergence of various types of fast food that do not pay attention to the correct way of cooking with recipes, methods, and processes according to Health standards. Culinary is an alternative business that is very promising and supports the community's economy and a culinary tourism trend that is currently in great demand by all groups. From these problems, we need a learning community in the field of culture that can be a solution. The learning community components are seen from four perspectives, namely, explore where the author uses the SECI model, and explain where knowledge is disseminated through mobile learning with features tailored to user needs. The practice begins with selecting the recipe, the ingredients used, the cooking process, validation, and feedback from the participants. And the engage perspective obtained good interaction from participants and to produce new recipes requires learning that is done repeatedly by combining various recipes, ingredients, and methods so that new recipes are produced that have unique and interesting characteristics and have taste, aroma and deliciousness and good nutritional value. The number of references used were 72 papers sourced from journals as many as 54 papers (75%) and the remaining 18 papers (25%) sourced from conferences, websites & white papers, and research reports. There were 15 papers published in 1991 – 2010 and 2011 – 2021 as many as 57 papers. This research is still limited to the learning community component in the culinary field, seen from four perspectives, and has not discussed the model that has been validated by experts. Participant motivation and learning outcomes will be discussed in the next research

Informal education will be successful as an alternative for the community because not all people are able to receive formal education. This study uses a qualitative method with a systematic literature review (SLR) technique to look for learning community components in informal education to support learning in the culinary community in the new normal era of Covid-19. The author collects, studies, and analyzes reference sources according to the specified keywords. Found 53 papers from 2002 to 2021 with background authors from academia, industry, and the public sector with reference sources from journals, conferences, white papers, and research reports. Systematic literature review results obtained 6 components of learning community in informal education, namely content, forum, method, technology, figure/layout, and human/social resources. The six components as a reference and the author's first step in the next research through searching for the characteristics of the learning community in the culinary field, then making a learning model of the culinary community. Because of the importance of the learning community component in informal education to help community members share knowledge, solve problems, share common goals and interests among community members.